Learning-Bayesian-Statistics/baygent-skills

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

A Python library that helps data scientists to infer causation rather than observing correlation.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Database with posteriors of interest for Bayesian inference

Open-source AI agent for scientific research. Analyze data in Python/R with Claude, GPT, Gemini, and more.

An AI-powered data science team of agents to help you perform common data science tasks 10X faster.

Expert-thinking AGENTS.md profiles that teach AI agents to reason like senior scientists and engineers.

A Python sandbox for decision making in dynamics